Millimeter wave imaging sensor arrays have been used to detect energy present in an imaging focal plane. These prior art sensor arrays produce images by directly sensing the energy in the focal plane, and each detector in the sensor array corresponds to one pixel in the image. Thus, sensitivity for these prior art sensors is limited by the noise at each sensor and by the amount of energy collected by each sensor. An example of such an array structure is disclosed in U.S. Pat. No. 6,828,556 to Pobanz et al. Another example of such an imaging sensor array is disclosed in “A Wideband Radiometer Module for an Unamplified Direct Detection Scalable W-band Imaging Array”, by James H. Schaffner et al., Proc. SPIE Vol. 6948, 694807 (2008).
Compressive sampling, also known as compressive sensing and sparse sampling, is another prior art technique that has been used to sense energy in a scene. The key concept of compressive sampling is to exploit the structure and redundancy in an image. The advantage of compressive sampling is that a detector is not needed for each pixel to obtain a particular image resolution and thus this technique promises to be less expensive than requiring a detector in the sensor array corresponding to each pixel in the image.
Such a technique is described in “Single-Pixel Imaging via Compressive Sampling” by M. F. Duarte, et al., IEEE Signal Processing Magazine, Vol. 25, No. 2, pp. 83-91, 2008. The described device consists of a digital micromirror device, two lenses, a single photon detector, and an analog-to-digital (A/D) converter that computes pseudo-random linear measurements of the scene under view. The image is then recovered by processing the measurements with a digital computer. The technique utilizes spatial light modulators or mirrors to modulate the signals at the optical visible wavelengths.
The compressive sampling technique described by Duarte utilizes a single “pixel” to detect the combined signals from all of the modulators or mirrors. For the compressive sampling technique to work in typical situations with moderate to low signal-to-noise ratio (SNR), the single “pixel” must be able to detect a large number of electromagnetic modes so that the resulting signal power is larger than that for a single mode. EM modes are an orthogonal set of EM field patterns that describe the manner in which energy is radiated from or absorbed by an electrically active device, including antenna elements, antenna arrays, antenna-coupled detectors, and photodetectors. EM modes are further described in “Performance Limitations of Compressive Sensing for Millimeter Wave Imaging” by Jonathan Lynch, Roy Matic, and Joshua Baron, Proc. SPIE 7670, 7670D 2010, which is incorporated herein by reference as though set forth in full. Detecting a large number of electromagnetic modes is relatively easy to accomplish at visible wavelengths, because electrically large multi-mode detectors are common and convenient. However, millimeter wave detectors typically detect only a single mode, so employing the prior art single “pixel” technique of Duarte would result in a significant attenuation of the image and a poor signal to noise ratio, and thus poor image quality.
Research, such as described by Duarte, has focused on imaging at visible or infrared wavelengths and used moveable mirrors as the method to implement compressive sensing. At visible wavelengths, which are 1 micron or less, the movable mirrors used for single “pixel” compressive sampling generally have a size of about 50 wavelengths or about 50 microns, in order to achieve an electrically large multi-mode detector. Millimeter wavelengths are on the order of 3 millimeters, so a mirror size of 50 wavelengths would be 150 millimeters or about 5.9 inches in size, which makes this approach impractical for millimeter wave imaging.
What is needed is a device that provides detection of multiple independent modes to obtain a high signal to noise ratio and high sensed image quality for imaging sensors and in particular imaging sensors for millimeter wavelengths, while providing the benefits of compressive sensing. The embodiments of the present disclosure answer these and other needs.